“In-memory computing is an attractive alternative for handling data-intensive tasks as it employs parallel processing without the need for data transfer. Nevertheless, it necessitates a high-density ...

A new technical paper titled “Embedding security into ferroelectric FET array via in situ memory operation” was published by researchers at Pennsylvania State University, University of Notre Dame, ...

A Nature paper describes an innovative analog in-memory computing (IMC) architecture tailored for the attention mechanism in large language models (LLMs). They want to drastically reduce latency and ...

Researchers have developed a new type of memory cell that can both store information and do high-speed, high-efficiency calculations. The memory cell enables users to run high-speed computations ...

TetraMem Inc., a Silicon Valley–based semiconductor company developing analog in-memory computing (IMC) solutions, today announced the successful tape-out, manufacturing, and initial silicon ...

A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling energy-efficient self-organizing maps without external arithmetic circuits. Memristors, ...

Machine learning (ML), a subset of artificial intelligence (AI), has become integral to our lives. It allows us to learn and reason from data using techniques such as deep neural network algorithms.

For decades, compute architectures have relied on dynamic random-access memory (DRAM) as their main memory, providing temporary storage from which processing units retrieve data and program code. The ...

The big picture: If successfully scaled to industrial production, these chips could extend Moore's Law into the atomic domain by enabling far greater component density without incurring unsustainable ...